ABSTRACT Enzyme activities are important biomarkers for cancer diagnoses and assessing chemotherapies. We have developed MRI contrast agents that are detected via Chemical Exchange Saturation Transfer (CEST) and that are responsive to enzyme activity. We have also developed CEST MRI methods that can detect these agents within in vivo tumor tissues in mouse models of human cancers. Importantly, we can selectively detect an enzyme-responsive agent and an unresponsive control agent during the same study in the same tissue location, which improves our evaluation of enzyme activity within the mouse model. Just as multiple fluorophores have revolutionized the evaluation of enzyme activities during in vitro and ex vivo studies, CEST agents and CEST MRI has potential to revolutionize the evaluation of enzyme activities in vivo. We propose to build on our recent research successes by linking enzyme-responsive and control agents to create a dimeric agent, by comparing paramagnetic and diamagnetic CEST agents, and by optimizing the saturation period of the CEST MRI acquisition protocol in order to improve the detection sensitivity of CEST MRI. We also propose to develop enzyme-responsive CEST agents that semi-quantitatively detect the activities of urokinase Plasminogen Activator (uPA) in mouse models of pancreatic cancer, Prostate Specific Membrane Antigen (PSMA) in mouse models of prostate cancer, and transglutaminase (TG2) in mouse models of breast cancer. We propose to use these CEST agents and our in vivo CEST MRI methodology to investigate three biomedical aims: A) to predict the effect of chemotherapies before they are administered to mouse models; B) to evaluate early response to chemotherapies; C) to investigate our hypothesis that enzyme activity is a more accurate biomarker than enzyme expression for predicting and evaluating therapeutic effects. Together, these studies address our overarching goal of eventually using CEST agents and CEST MRI to tailor the choice of chemotherapy and treatment regimen for each individual patient, in order to support the paradigm of personalized medicine.